Build local AI decision flows without token costs
Developers can use rizzo-flow to build typed AI decision processes that run locally without generating tokens.
Open NuviFlux for the evidence, open questions, and first test.
THE OPPORTUNITY, IN CONTEXT
Build local AI decision flows without token costs
The business model
Some workflows need a category or routing decision, not a long generated answer. A local-model integration could handle one such task, provided its errors and uncertain inputs are acceptable for the intended use.
What has been observed
Rizzo Flow describes local typed LLM decisions without token generation. This is a technical claim about its approach, not proof of accuracy for every task or zero operating cost.
Entry conditions and costs
Hardware, setup, model compatibility and maintenance still carry costs. Incorrect decisions and uncertain inputs limit suitability for consequential automation.
The key question
Can the local decisions meet the team's needs without unacceptable errors?
Common questions
Does no token generation mean no cost?
No. Compute, setup and maintenance still have costs.
Is accuracy established for every task?
Task-specific accuracy and model support remain unverified.
A CLOSER LOOK
Build local AI decision flows without token costs
Some workflows need a short decision rather than a generated answer. Developers could offer local classification or routing integrations for tasks with manageable error risks.
